From Patient Records to Real-World Evidence

A question after the clinic visit

Imagine a patient leaving a clinic with a new medicine. At the next visit, the doctor records how the patient feels. A pharmacy records a refill. Months later, a hospital records an admission.

Each record tells part of the story. Could these pieces help us learn how care works in daily life?

This is the idea behind real-world evidence, or RWE. But the idea did not begin with a large database. Its roots go back to an older practice: watching what happens to people over time and asking careful questions.

Two paths to learning

To understand the journey, let us go back to 1948.

In Britain, researchers published a landmark trial of streptomycin, a drug used to treat tuberculosis. Patients were assigned by chance to groups so that researchers could make a fairer comparison of treatment. This was an important step in the growth of randomized clinical trials.

That same year, the Framingham Heart Study began in Massachusetts. Researchers followed people over time to learn which factors were linked to heart disease. The study helped build our knowledge of risks such as high blood pressure, smoking, and high cholesterol.

These studies took different paths. One assigned treatment and compared groups. The other followed people and looked for patterns in their health.

Framingham was a planned research study with its own exams. It was not simply a modern database of routine medical records. Still, it shows that learning from people over time was important long before the term RWE became common.

Trials answered questions. Daily care raised more.

In a clinical trial, researchers assign a treatment or another intervention under a study plan. In a randomized trial, assignment happens by chance. This helps reduce differences between groups that could affect the results.

Trials are a key way to learn whether a treatment causes a benefit or harm. But any one trial has limits. It studies certain people for a certain period under a set plan.

What happens when care reaches people with other health conditions? What happens over a longer period? How is a medicine used when choices are made during normal care?

These questions helped drive interest in using information from everyday healthcare alongside trial findings. FDA researchers have explained why RWE and trial evidence should not be treated as two separate worlds.

First, what is RWD?

RWD means real-world data. In simple terms, these are health and care records collected routinely from sources such as clinics, insurance systems, and registries.

A blood pressure reading is data. A prescription record is data. A patient's report of symptoms during routine care can also be data.

RWE is what researchers learn from studying suitable RWD with a clear question and sound methods. FDA uses the term for clinical evidence about a medical product's use and possible benefits or risks.

The distinction is simple: records provide the information; research turns that information into evidence. A file full of records is not proof that a treatment works.

Where do the data come from?

Several sources can help tell the story. Each has strengths and gaps.

• Medical records: Clinic and hospital records may contain diagnoses, test results, treatments, and doctors' notes. Care received elsewhere may be missing.
• Insurance claims: These records are created for billing and payment. They can show visits, procedures, and costs, but may lack the detail needed to explain why care was given.
• Pharmacy records: These can show that a medicine was dispensed. They do not prove that a person took every dose.
• Disease or product registries: These collect information about people with a condition or people using a certain treatment or device. What they can answer depends on what they collect and who is included.
• Patient reports and health devices: Symptom reports, home readings, and wearable devices may add information about daily health. Their use and quality need to be checked. A device reading is not automatically suitable for every research question.

Data also come in different forms. A lab value or diagnosis code is structured data, stored in set fields. A doctor's written note is unstructured data and may need more work to study. A study can look back at existing records or collect routine-care data going forward. How the data are collected matters; not every survey or digital record counts as RWD.

How modern RWE took shape

As more health information became digital, researchers gained new ways to study care across settings. There was also a growing need to keep checking medical products after approval.

In 2008, FDA launched the Sentinel Initiative to improve medical product safety monitoring. It built on FDA's earlier use of insurance and healthcare records to study safety questions. Everyday care was already helping answer questions about medicines before the recent growth of the RWE field.

Then came a major U.S. policy step. The 21st Century Cures Act of 2016 called for a program to explore certain uses of RWE in drug decisions. FDA issued its framework in 2018.

The law did not invent RWE. It gave a stronger formal role to work with much older roots. Modern RWE grew through better access to data, stronger study methods, and clearer expectations for how evidence should be assessed.

Does RWE need a large dataset?

No. Size alone does not define RWE or make it useful.

Imagine a team studying a rare disease. A small registry may contain the exact test results and follow-up details the team needs. A much larger database may not capture those facts at all.

That does not mean small studies are always enough. A small sample may give uncertain results or miss rare events. Some questions need many patients and years of follow-up.

The right size depends on the question, the study design, how often the outcome occurs, and how precise the answer needs to be. More records cannot fix a key fact that was never collected.

FDA's guidance stresses the relevance and reliability of data for the question being asked. At Master Table, our starting questions are practical: Do these records include the right people? Can we measure what matters? Are the dates and follow-up clear? What is missing?

How is RWE different from a clinical trial?

A clinical trial is a way to design a study. RWE describes evidence drawn from real-world data. They can overlap.

In an observational RWE study, researchers do not assign the treatment being studied. They examine care choices already made by patients and clinicians. This can make comparisons difficult. For example, one treatment group may have been sicker before treatment began.

A randomized trial assigns treatment by chance. It can also use routine medical records to find people or track outcomes.

The ADAPTABLE study is one example. It randomly assigned patients to two aspirin doses and used electronic health records, claims, and patient reports in its research. It shows how randomization and real-world data can work together.

The words "real world" do not mean that trial patients are less real. They describe where and how the data are collected.

Good evidence still needs a plan

Imagine that patients receiving Medicine A have fewer hospital stays than patients receiving Medicine B. Did Medicine A cause that difference? Or were its users healthier at the start?

A strong study must examine such questions. It needs clear rules for who is included, when follow-up starts, what is measured, and how groups are compared. The analysis must also explain uncertainty and limits. A large number of records does not remove bias.

This is why the protocol and statistical analysis plan matter. They connect the question to the work, before the team draws conclusions.

Master Table supports that process through study design, protocols, analysis plans, RWE research, and scientific writing. We aim to help teams use the right data for the right question and explain what the results can support.

The journey from a patient record to useful evidence takes more than a database. It takes a question worth answering and a careful plan to answer it.

To discuss an RWE study, contact hello@mastertable.com.

References

1. Medical Research Council. (1948). Streptomycin Treatment of Pulmonary Tuberculosis. British Medical Journal, 2, 769-782.
2. National Heart, Lung, and Blood Institute. Framingham Heart Study.
3. Concato J, Corrigan-Curay J. (2022). Real-World Evidence — Where Are We Now? New England Journal of Medicine, 386, 1680-1682.
4. U.S. Food and Drug Administration. Real-World Evidence. Definitions and background on the FDA program.
5. NIH Pragmatic Trials Collaboratory. Common Real-World Data Sources.
6. U.S. Food and Drug Administration. FDA's Sentinel Initiative — Background.
7. U.S. Food and Drug Administration. (2024). Real-World Data: Assessing Electronic Health Records and Medical Claims Data to Support Regulatory Decision-Making for Drug and Biological Products.
8. Duke Clinical Research Institute. (2020). Paper Details Design of ADAPTABLE, First Pragmatic Trial to Use PCORnet. See also Jones WS, et al. (2021). Comparative Effectiveness of Aspirin Dosing in Cardiovascular Disease. New England Journal of Medicine.

Sources reviewed September 26, 2026. The clinic visit, rare-disease registry, and Medicine A/B examples are hypothetical. This article highlights selected milestones, not a complete history of observational research.